Awesome

📹🎙️🐍 Python SDK for LiveKit

Use this SDK to add realtime video, audio and data features to your Python app. By connecting to <a href="https://livekit.io/">LiveKit</a> Cloud or a self-hosted server, you can quickly build applications such as multi-modal AI, live streaming, or video calls with just a few lines of code.

This repo contains two packages

• livekit: Real-time SDK for connecting to LiveKit as a participant
• livekit-api: Access token generation and server APIs

Using Server API

$ pip install livekit-api

Generating an access token

from livekit import api
import os

# will automatically use the LIVEKIT_API_KEY and LIVEKIT_API_SECRET env vars
token = api.AccessToken() \
    .with_identity("python-bot") \
    .with_name("Python Bot") \
    .with_grants(api.VideoGrants(
        room_join=True,
        room="my-room",
    )).to_jwt()

Creating a room

RoomService uses asyncio and aiohttp to make API calls. It needs to be used with an event loop.

from livekit import api
import asyncio

async def main():
    lkapi = api.LiveKitAPI(
        'http://localhost:7880',
    )
    room_info = await lkapi.room.create_room(
        api.CreateRoomRequest(name="my-room"),
    )
    print(room_info)
    results = await lkapi.room.list_rooms(api.ListRoomsRequest())
    print(results)
    await lkapi.aclose()

asyncio.get_event_loop().run_until_complete(main())

Using Real-time SDK

$ pip install livekit

Connecting to a room

from livekit import rtc

async def main():
    room = rtc.Room()

    @room.on("participant_connected")
    def on_participant_connected(participant: rtc.RemoteParticipant):
        logging.info(
            "participant connected: %s %s", participant.sid, participant.identity)

    async def receive_frames(stream: rtc.VideoStream):
        async for frame in video_stream:
            # received a video frame from the track, process it here
            pass

    # track_subscribed is emitted whenever the local participant is subscribed to a new track
    @room.on("track_subscribed")
    def on_track_subscribed(track: rtc.Track, publication: rtc.RemoteTrackPublication, participant: rtc.RemoteParticipant):
        logging.info("track subscribed: %s", publication.sid)
        if track.kind == rtc.TrackKind.KIND_VIDEO:
            video_stream = rtc.VideoStream(track)
            asyncio.ensure_future(receive_frames(video_stream))

    # By default, autosubscribe is enabled. The participant will be subscribed to
    # all published tracks in the room
    await room.connect(URL, TOKEN)
    logging.info("connected to room %s", room.name)

    # participants and tracks that are already available in the room
    # participant_connected and track_published events will *not* be emitted for them
    for participant in room.participants.items():
        for publication in participant.track_publications.items():
            print("track publication: %s", publication.sid)

Sending and receiving chat

room = rtc.Room()
...

chat = rtc.ChatManager(room)

# receiving chat
@chat.on("message_received")
def on_message_received(msg: rtc.ChatMessage):
    print(f"message received: {msg.participant.identity}: {msg.message}")

# sending chat
await chat.send_message("hello world")

Examples

• Facelandmark: Use mediapipe to detect face landmarks (eyes, nose ...)
• Basic room: Connect to a room
• Publish hue: Publish a rainbow video track
• Publish wave: Publish a sine wave

Getting help / Contributing

Please join us on Slack to get help from our devs / community members. We welcome your contributions(PRs) and details can be discussed there.

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